In analyzing and processing data acquired in real time from external sources, it may often be useful and/or efficient to process only a portion of the data relative to a certain set of data that may be recursively acquired, such as data relative to a certain limited area of images acquired in sequence (video images), for example. This way of operating is common in many applications, such as in the following: quality analysis systems security overseeing systems (environmental, territorial, etc.), safety systems, biomedical survey, and automotive.
The processing of acquired matrices of data (data arrays) requires a calculation power proportioned to their size. However, in certain applications or for certain objectives, the analysis and the processing could be limited to specific portions of sets of data organized in matrices, i.e., of data-arrays, instead of processing whole data-arrays to reduce the calculation power required.
Clearly, such a selection of a limited portion of each acquired data array will depend on the specific needs and on the objectives of the application. In case there are sets of data that are recursively updated, such a selection is performed only after having acquired all the data. This implies the use of a system designed ad hoc, which results in a waste of time and resources that limits enhancement of overall process speed. In fact, a non-negligible portion of the calculated power performs the extraction operation.
The portion of data to be extracted is often predefined, therefore, the selection parameters that identify it are stored. Selection parameters include a first row of the portion to be extracted of the data-array, the number of rows of the portion, the column index of a first value of the first row, the number of values of the row to be considered and (in case the perimeter segments of the region to be selected are not orthogonal to the reference axis of the data-array) also the slope of the perimeter segments, and the number of values to be extracted. Of course, for each row of the selected portion, it is thus necessary to identify these values and calculate the positions of other data to be extracted. The more numerous the distinct portions to be extracted results in, more sets of selection parameters being stored.